Research Scientist (Human-AI Systems)

Join Snorkel, a leading company in data-centric AI. As a Research Scientist, you will advance the creation of high-quality data and environments for AI agents. You will design and optimize reusable pipelines, run rigorous experiments, and partner with various teams to turn research prototypes into reliable production workflows. This role is ideal for someone with a strong research background in AI and machine learning, and experience in building environments for AI agents. Enjoy comprehensive benefits, unlimited PTO, and the opportunity to work with a global team.

- Concevoir, mettre en œuvre et optimiser des pipelines réutilisables qui combinent les capacités de l'IA avec le jugement d'experts pour accélérer la création de données et d'environnements agentiques. - Collaborer avec des experts en la matière, des partenaires académiques, des clients et nos équipes produit et ingénierie pour étendre ces pipelines et cibler les lacunes de performance des modèles de pointe. - Rester à la pointe de la recherche dans la création de données et d'environnements agentiques et intégrer les meilleures pratiques dans les flux de travail de Snorkel.

- This role is ideal for someone who wants to advance frontier AI through data and environment creation and enjoys turning research into reusable, scalable systems - Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered - Experience with one or more of synthetic data generation, human in the loop workflows, reinforcement learning, agent environments, or model evaluation - Experience building environments for AI agents in automated research, computer use, coding, or professional domain workflows - Experience with software engineering best practices (e.g., clean coding, modular design, version control) - Ability to collaborate with domain experts and translate their knowledge into concrete tasks, evaluation criteria, and repeatable workflows - Comfort with rapid iteration, ambiguous research questions, and moving ideas from experimentation into production - Strong research background in AI, machine learning, NLP, LLMs, or related fields, with experience developing and evaluating new methods - Strong experimental design skills, including defining hypotheses and conducting ablations